Remove AI Remove Data Pipeline Remove DataOps
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Five Important Trends in Big Data Analytics

Flipboard

Over the last few years, with the rapid growth of data, pipeline, AI/ML, and analytics, DataOps has become a noteworthy piece of day-to-day business New-age technologies are almost entirely running the world today. Among these technologies, big data has gained significant traction. This concept is …

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What Is DataOps? Definition, Principles, and Benefits

Alation

What exactly is DataOps ? The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively.

DataOps 52
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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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Building and Scaling Gen AI Applications with Simplicity, Performance and Risk Mitigation in Mind Using Iguazio (acquired by McKinsey) and MongoDB

Iguazio

AI and generative Al can lead to major enterprise advancements and productivity gains. One popular gen AI use case is customer service and personalization. Gen AI chatbots have quickly transformed the way that customers interact with organizations. Another less obvious use case is fraud detection and prevention.

AI 132
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The Audience for Data Catalogs and Data Intelligence

Alation

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. ML and DataOps teams). data pipelines) to support.

DataOps 52
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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

Big Data 106
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How HR Tech Company Sense Scaled their ML Operations using Iguazio

Iguazio

Sense is a talent engagement company whose platform improves the recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals.

ML 52